MODEL PROFILE

LVFace

bytedance-research · LVFace

--> This is the official PyTorch implementation for the inference of LVFace. Drawing inspiration from the massive data support, multi-stage training paradigm, and Transformer architecture of large-model technology, this method, based on Large Vision Transformer, has carried out progressive optimization of the face clustering space through multiple stages on massive datasets. --> - 🔥🔥🔥 We have released the training weights of LVFace. Please click here to download it. (August, 2025 UTC) - 🎉🎉🎉 LVFace has been recommended as **ICCV Highlight**. (July, 2025 UTC) - 🎉🎉🎉 LVFace is accepted by **ICCV 2025**. (July, 2025 UTC) - 🔥🔥🔥 We have updated the arXiv report of LVFace. Please click here to view it. (March, 2025 UTC) - 🎉🎉🎉 LVFace secured **1st place** in the ICCV 2021 Masked Face Recognition (MFR)-Ongoing Challenge (academic track). (December, 2024 UTC) Test datasets for inference validation can be downloaded from the following sources: - **IJB-C & IJB-B**: Google Drive - **MFR-Ongoing**: Challenge Page

license:mit
Context windowNot disclosed
Input → Output待核验 → 待核验
Model weightsNot verified
Profile updated2026/11/2 19:15:55
OVERVIEW

Model overview

--> This is the official PyTorch implementation for the inference of LVFace. Drawing inspiration from the massive data support, multi-stage training paradigm, and Transformer architecture of large-model technology, this method, based on Large Vision Transformer, has carried out progressive optimization of the face clustering space through multiple stages on massive datasets. --> - 🔥🔥🔥 We have released the training weights of LVFace. Please click here to download it. (August, 2025 UTC) - 🎉🎉🎉 LVFace has been recommended as **ICCV Highlight**. (July, 2025 UTC) - 🎉🎉🎉 LVFace is accepted by **ICCV 2025**. (July, 2025 UTC) - 🔥🔥🔥 We have updated the arXiv report of LVFace. Please click here to view it. (March, 2025 UTC) - 🎉🎉🎉 LVFace secured **1st place** in the ICCV 2021 Masked Face Recognition (MFR)-Ongoing Challenge (academic track). (December, 2024 UTC) Test datasets for inference validation can be downloaded from the following sources: - **IJB-C & IJB-B**: Google Drive - **MFR-Ongoing**: Challenge Page

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

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Frequently asked questions

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Sources & traceability

许可证:mit。模型介绍与第三方评测均以原来源的具体版本和方法为准。